So when Google ultimately retired Glass, it was in reaction to an important act of line drawing. It was an admission of defeat not by design, but by culture.

These kinds of skirmishes on the front lines of surveillance might seem inconsequential — but they can not only change the behavior of tech giants like Google, they can also change how we’re protected under the law. Each time we invite another device into our lives, we open up a legal conversation over how that device’s capabilities change our right to privacy. To understand why, we have to get wonky for a bit, but it’s worth it, I promise.

But where many people see Google Glass as a cautionary tale about tech adoption failure, I see a wild success. Not for Google of course, but for the rest of us. Google Glass is a story about human beings setting boundaries and pushing back against surveillance…

IN THE UNITED States, the laws that dictate when you can and cannot record someone have a several layers. But most of these laws were written when smartphones and digital home assistants weren’t even a glimmer in Google’s eye. As a result, they are mostly concerned with issues of government surveillance, not individuals surveilling each other or companies surveilling their customers. Which means that as cameras and microphones creep further into our everyday lives, there are more and more legal gray zones.

From DSC:We need to be aware of the emerging technologies around us. Just because we can, doesn’t mean we should. People need to be aware of — and involved with — which emerging technologies get rolled out (or not) and/or which features are beneficial to roll out (or not).

One of the things that’s beginning to alarm me these days is how the United States has turned over the keys to the Maserati — i.e., think an expensive, powerful thing — to youth who lack the life experiences to know how to handle such power and, often, the proper respect for such power. Many of these youthful members of our society don’t own the responsibility for the positive and negative influences and impacts that such powerful technologies can have.

If you owned the car below, would you turn the keys of this ~$137,000+ car over to your 16-25 year old? Yet that’s what American has been doing for years. And, in some areas, we’re now paying the price.

The corporate world continues to discard the hard-earned experience that age brings…as they shove older people out of the workforce. (I hesitate to use the word wisdom…but in some cases, that’s also relevant/involved here.) Then we, as a society, sit back and wonder how did we get to this place?

Even technologists and programmers in their 20’s and 30’s are beginning to step back and ask…WHY did we develop this application or that feature? Was it — is it — good for society? Is it beneficial? Or should it be tabled or revised into something else?

Below is but one example — though I don’t mean to pick on Microsoft, as they likely have more older workers than the Facebooks, Googles, or Amazons of the world. I fully realize that all of these companies have some older employees. But the youth-oriented culture in American today has almost become an obsession — and not just in the tech world. Turn on the TV, check out the new releases on Netflix, go see a movie in a theater, listen to the radio, cast but a glance at the magazines in the check out lines, etc. and you’ll instantly know what I mean.

In the workplace, there appears to be a bias against older employees as being less innovative or tech-savvy — such a perspective is often completely incorrect. Go check out LinkedIn for items re: age discrimination…it’s a very real thing. But many of us over the age of 30 know this to be true if we’ve lost a job in the last decade or two and have tried to get a job that involves technology.

On Thursday, the American Civil Liberties Union provided a good reason for us to think carefully about the evolution of facial-recognition technology. In a study, the group used Amazon’s (AMZN) Rekognition service to compare portraits of members of Congress to 25,000 arrest mugshots. The result: 28 members were mistakenly matched with 28 suspects.

The ACLU isn’t the only group raising the alarm about the technology. Earlier this month, Microsoft (MSFT) president Brad Smith posted an unusual plea on the company’s blog asking that the development of facial-recognition systems not be left up to tech companies.

Saying that the tech “raises issues that go to the heart of fundamental human rights protections like privacy and freedom of expression,” Smith called for “a government initiative to regulate the proper use of facial recognition technology, informed first by a bipartisan and expert commission.”

Meredith Whittaker , AI Now Institute, New York University, Google Open Research
Kate Crawford , AI Now Institute, New York University, Microsoft Research
Roel Dobbe , AI Now Institute, New York University
Genevieve Fried , AI Now Institute, New York University
Elizabeth Kaziunas , AI Now Institute, New York University
Varoon Mathur , AI Now Institute, New York University
Sarah Myers West , AI Now Institute, New York University
Rashida Richardson , AI Now Institute, New York University
Jason Schultz , AI Now Institute, New York University School of Law
Oscar Schwartz , AI Now Institute, New York University

With research assistance from Alex Campolo and Gretchen Krueger (AI Now Institute, New York University)

Excerpt (emphasis DSC):

Building on our 2016 and 2017 reports, the AI Now 2018 Report contends with this central problem, and provides 10 practical recommendationsthat can help create accountability frameworks capable of governing these powerful technologies.

Governments need to regulate AI by expanding the powers of sector-specific agencies to oversee, audit, and monitor these technologies by domain.

Facial recognition and affect recognition need stringent regulation to protect the public interest.

The AI industry urgently needs new approaches to governance. As this report demonstrates, internal governance structures at most technology companies are failing to ensure accountability for AI systems.

AI companies should waive trade secrecy and other legal claims that stand in the way of accountability in the public sector.

Technology companies must go beyond the “pipeline model” and commit to addressing the practices of exclusion and discrimination in their workplaces.

Fairness, accountability, and transparency in AI require a detailed account of the “full stack supply chain.”

More funding and support are needed for litigation, labor organizing, and community participation on AI accountability issues.

University AI programs should expand beyond computer science and engineering disciplines.AI began as an interdisciplinary field, but over the decades has narrowed to become a technical discipline. With the increasing application of AI systems to social domains, it needs to expand its disciplinary orientation. That means centering forms of expertise from the social and humanistic disciplines. AI efforts that genuinely wish to address social implications cannot stay solely within computer science and engineering departments, where faculty and students are not trained to research the social world. Expanding the disciplinary orientation of AI research will ensure deeper attention to social contexts, and more focus on potential hazards when these systems are applied to human populations.

As we discussed, this technology brings important and even exciting societal benefits but also the potential for abuse. We noted the need for broader study and discussion of these issues. In the ensuing months, we’ve been pursuing these issues further, talking with technologists, companies, civil society groups, academics and public officials around the world. We’ve learned more and tested new ideas. Based on this work, we believe it’s important to move beyond study and discussion. The time for action has arrived.

We believe it’s important for governments in 2019 to start adopting laws to regulate this technology. The facial recognition genie, so to speak, is just emerging from the bottle. Unless we act, we risk waking up five years from now to find that facial recognition services have spread in ways that exacerbate societal issues. By that time, these challenges will be much more difficult to bottle back up.

In particular, we don’t believe that the world will be best served by a commercial race to the bottom, with tech companies forced to choose between social responsibility and market success. We believe that the only way to protect against this race to the bottom is to build a floor of responsibility that supports healthy market competition. And a solid floor requires that we ensure that this technology, and the organizations that develop and use it, are governed by the rule of law.

From DSC:This is a major heads up to the American Bar Association (ABA), law schools, governments, legislatures around the country, the courts, the corporate world, as well as for colleges, universities, and community colleges. The pace of emerging technologies is much faster than society’s ability to deal with them!

The ABA and law schools need to majorly pick up their pace — for the benefit of all within our society.

Alongside Geoff Hinton and Yann LeCun, Bengio is famous for championing a technique known as deep learning that in recent years has gone from an academic curiosity to one of the most powerful technologies on the planet.

Deep learning involves feeding data to large neural networks that crudely simulate the human brain, and it has proved incredibly powerful and effective for all sorts of practical tasks, from voice recognition and image classification to controlling self-driving cars and automating business decisions.

Bengio has resisted the lure of any big tech company. While Hinton and LeCun joined Google and Facebook, respectively, he remains a full-time professor at the University of Montreal. (He did, however, cofound Element AI in 2016, and it has built a very successful business helping big companies explore the commercial applications of AI research.)

What do you make of the idea that there’s an AI race between different countries?

I don’t like it. I don’t think it’s the right way to do it.

We could collectively participate in a race, but as a scientist and somebody who wants to think about the common good, I think we’re better off thinking about how to both build smarter machines and make sure AI is used for the well-being of as many people as possible.

China’s plan to judge each of its 1.3 billion people based on their social behavior is moving a step closer to reality, with Beijing set to adopt a lifelong points program by 2021 that assigns personalized ratings for each resident.

The capital city will pool data from several departments to reward and punish some 22 million citizens based on their actions and reputations by the end of 2020, according to a plan posted on the Beijing municipal government’s website on Monday. Those with better so-called social credit will get “green channel” benefits while those who violate laws will find life more difficult.

The Beijing project will improve blacklist systems so that those deemed untrustworthy will be “unable to move even a single step,” according to the government’s plan.

From DSC:Matthew 18:21-35 comes to mind big time here! I’m glad the LORD isn’t like this…we would all be in trouble.

A collective eyebrow was raised by the AI and robotics community when the robot Sophia was given Saudia citizenship in 2017 The AI sharks were already circling as Sophia’s fame spread with worldwide media attention. Were they just jealous buzz-kills or is something deeper going on? Sophia has gripped the public imagination with its interesting and fun appearances on TV and on high-profile conference platforms.

Sophia is not the first show robot to attain celebrity status. Yet accusations of hype and deception have proliferated about the misrepresentation of AI to public and policymakers alike. In an AI-hungry world where decisions about the application of the technologies will impact significantly on our lives, Sophia’s creators may have crossed a line. What might the negative consequences be? To get answers, we need to place Sophia in the context of earlier show robots.

A dangerous path for our rights and securityFor me, the biggest problem with the hype surrounding Sophia is that we have entered a critical moment in the history of AI where informed decisions need to be made. AI is sweeping through the business world and being delegated decisions that impact significantly on peoples lives from mortgage and loan applications to job interviews, to prison sentences and bail guidance, to transport and delivery services to medicine and care.

It is vitally important that our governments and policymakers are strongly grounded in the reality of AI at this time and are not misled by hype, speculation, and fantasy. It is not clear how much the Hanson Robotics team are aware of the dangers that they are creating by appearing on international platforms with government ministers and policymakers in the audience.

We think of this as a transformation away from a mass-production model to a mass-personalization model. For us, that’s the big win in this whole process. When we move away from the large lectures in that mass-production model that we’ve used for the last 170 years and get into something that reflects each of the individual learners’ needs and can personalize their learning path through the instructional resources, we will have successfully moved the education industry to the new frontier in the learning process. We think that mass personalization has already permeated every aspect of our lives, from navigation to entertainment; and education is really the next big frontier.

From DSC:Each year the vision I outlined here gets closer and closer and closer and closer. With the advancements in Artificial Intelligence (AI), change is on the horizon…big time. Mass personalization. More choice. More control.

A few years ago, in a move toward professional learning, LinkedIn bought Lynda.com for $1.5 billion, adding the well-known library of video-based courses to its professional social network. Today LinkedIn officials announced that they plan to open up their platform to let in educational videos from other providers as well—but with a catch or two.

The plan, announced Friday, is to let companies or colleges who already subscribe to LinkedIn Learning add content from a select group of other providers. The company or college will still have to subscribe to those other services separately, so it’s essentially an integration—but it does mark a change in approach.

For LinkedIn, the goal is to become the front door for employees as they look for micro-courses for professional development.

LinkedIn also announced another service for its LinkedIn Learning platform called Q&A, which will give subscribers the ability to pose a question they have about the video lessons they’re taking. The question will first be sent to bots, but if that doesn’t yield an answer the query will be sent on to other learners, and in some cases the instructor who created the videos.

LinkedIn has become quite a juggernaut in the corporate learning market. Last time I checked the company had more than 17 million users, 14,000 corporate customers, more than 3,000 courses and was growing at high double-digit rates. And all this in only about two years.

And the company just threw down the gauntlet; it’s now announcing it has completely opened up its learning platform to external content partners. This is the company’s formal announcement that LinkedIn Learning is not just an amazing array of content, it is a corporate learning platform. The company wants to become a single place for all organizational learning content.

LinkedIn now offers skills-based learning recommendations to any user through its machine learning algorithms.

Is there demand for staying relevant? For learning new skills? For reinventing oneself?

From DSC:So…look out higher ed and traditional forms of accreditation — your window of opportunity may be starting to close. Alternatives to traditional higher ed continue to appear on the scene and gain momentum. LinkedIn — and/or similar organizations in the future — along with blockchain and big data backed efforts may gain traction in the future and start taking away some major market share. If employers get solid performance from their employees who have gone this route…higher ed better look out.

Meet the 83-Year-Old App Developer Who Says Edtech Should Better Support Seniors — from edsurge.com by Sydney JohnsonExcerpt (emphasis DSC):
Now at age 83, Wakamiya beams with excitement when she recounts her journey, which has been featured in news outlets and even at Apple’s developer conference last year. But through learning how to code, she believes that experience offers an even more important lesson to today’s education and technology companies: don’t forget about senior citizens.Today’s education technology products overwhelmingly target young people.And while there’s a growing industry around serving adult learners in higher education, companies largely neglect to consider the needs of the elderly.

Eastman Kodak, a leader for many years, filed for bankruptcy in 2012. Blockbuster Video became defunct in 2013. Similarly, Borders — one of the largest book retailers in the U.S. — went out of business in 2011. Why did these companies, which once had great brands, ultimately fail? It is because they failed to adapt to change. Additionally, they failed to unlearn and relearn.
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Former GE CEOJack Welch once remarked, “If the rate of change on the outside exceeds the rate of change on the inside, the end is near.” Thus, accept change before the change is thrust on you.
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Leaders must adopt tools and techniques to adapt to change. Here is a blueprint to embrace change effectively:

Keep the vision right and straight, and articulate it effectively.

Create organizational culture conducive to bring about change.

Communicate clearly about the need to change.

Enlighten people about the implications of the status quo.

Show them benefits once the change is implemented.

Coordinate all stakeholders effectively.

Remove the roadblocks by allaying their apprehensions.

Show them small gains to ensure that entire change takes place smoothly without any resistance.

From DSC:Though I’m not on board with all of the perspectives in that article, institutions of traditional higher education likely have something to learn from the failures of these companies….while there’s still time to change and to innovate.